Search Results (16,541)

The carpal gland is an important exocrine gland in pigs, functioning mainly through diverticula that release strongly odorous secretions. The size of the carpal gland and the number of diverticula may be related to its function. To measure its size, the gland must be dissected from the foreleg, and this procedure is time-consuming and cumbersome. The diverticulum is the outlet of the carpal gland, and its number correlates with the carpal gland size, but the correlation coefficient between them is still unknown. To explore the relationship between the size and diverticular number of the carpal gland, 788 pigs from four populations were used in this study. The length, width, thickness, weight and volume of the carpal gland were measured, together with its diverticular number. The phenotypic correlation coefficient between each pair of the recorded traits was calculated, and a two-factor analysis of variance was used to test whether sex and population have effects on the phenotypes. The carpal gland is a flat small stick with a length of 1.8–8.6 cm, width of 0.6–2.5 cm, and thickness of 0.2–0.8 cm, and its specific gravity is 0.51–1.36. Each carpal gland has 0 to 10 diverticula, and 82.3% carpal glands have 2–6 diverticula. The diverticular number correlates positively with the weight (r = 0.57 and r_s = 0.58, p < 2.2 × 10⁻¹⁶) and volume (r = 0.55 and r_s = 0.56, p < 2.2 × 10⁻¹⁶). Population and sex only explain 20% of the phenotypic variance, suggesting that the 80% of carpal gland influences remain unknown. In conclusion, the diverticular number can be used as a proxy for the weightand volume of the carpal gland, because it is easy to count and has a significant positive correlation with the size of thecarpal gland. Full article

Background/Objectives: Pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH) are complex diseases that require precise diagnosis and management. The ESC risk score has been used in both conditions. We assessed the relationship between the EmPHasis-10 questionnaire (patient subjective evaluation) and objective assessment using endorsed tools (simplified four-strata risk assessment and right ventricular imaging by transthoracic echocardiography). Methods: The present study retrospectively extracted data from 40 adult patients (27 PAH and 13 CTEPH cases) diagnosed in a single center in Romania. The EmPHasis-10 questionnaire and the four-strata risk assessment (FSRA) tool were applied to each patient. Mean pulmonary artery pressure (mPAP), tricuspid annular plane systolic excursion (TAPSE), TAPSE/systolic pulmonary artery pressure (TAPSE/sPAP) ratio, and right ventricular outflow tract acceleration time (RVOT-AT) were assessed. Results: A significant correlation was observed between the EmPHasis-10 scores and the FSRA tool, the WHO functional class, and the 6 min walking distance. Emphasis-10 score did not correlate with any of the echocardiographic parameters. The FSRA tool showed a moderate positive correlation with mPAP (r = 0.42, p = 0.01) and a negative correlation with TAPSE (r = −0.46, p = 0.003); additionally, across the entire cohort, it was moderately negatively correlated with both RVOT-AT (r = −0.42, p = 0.01) and TAPSE/sPAP ratio (r = −0.43, p = 0.005). Conclusions: Our study evidenced the alignment between EmPHasis-10 scores and prognostic risk score, with poorer health-related quality of life corresponding to higher FSRA. The EmPHasis-10 questionnaire proves to be a valuable, easy-to-use instrument, offering meaningful insights into patients’ health-related quality of life, underscoring its utility in enhancing comprehensive patient assessment and management. Full article

Surface-enhanced Raman spectroscopy is a powerful technique for the ultra-sensitive detection of organic analytes. In this paper, the preparation of SERS substrates based on silver nanorods (AgNRs) is proposed, exploiting a simple protocol which does not require complex procedures and/or sophisticated and expensive instrumentation. For this purpose, various syntheses of AgNRs were tested, and the best one for preparing the SERS active substrate proved to be the one which does not involve surfactants as nanoparticle stabilizers. The plasmonic properties of the selected substrate can be modified based on the concentration of the deposited nanoparticles, allowing for the experimentation of different excitation wavelengths. Positive results were obtained on reference solutions of three natural dyes of historical interest using both green exciting radiation (532 nm) and two near-infrared ones (785 and 850 nm; the latter is combined with the SSE™ technology for further fluorescence quenching). Furthermore, the substrates of AgNRs were found to be suitable for SERS measurements even in dry-state conditions, i.e., only exploiting the electromagnetic interaction between the nanostructured substrate and the dye molecules absorbed onto a wool fibre. Full article

An efficient and operationally simple method for the synthesis of α-acyloxy ketones through the readily available 2-methylimidazole-promoted reaction of α-hydroxy ketones and anhydrides is developed. In the reaction, the anhydrides act as both a substrate and a solvent. The new method features good substrate tolerance, mild reaction conditions, readily accessible starting materials, and excellent yields, providing facile and green access to the targets. Importantly, the reaction also avoids the use of reagents with pungent odors, such as pyridine, in traditional esterification, which may promote the development of organocatalysis using nitrogen-containing heterocyclic compounds as catalysts. Full article

This paper aims to help data center administrators choose thermal simulation tools, which manage thermal conduction from power for energy savings. When evaluating and suggesting data center thermal simulators for users, questions such as “What are the simulator’s differences? Are they easy to use? Which is the best choice?” are frequently asked. To answer these questions, this paper reviews the thermal simulation works for data centers in the last ten years. After that, it proposes the versatility and dexterity metrics for these simulators and discovers that it is difficult to choose them despite their similar design purpose and functions. Empowered by the survey, we claim that the widespread practice simulators still need more enhancement in data center scenarios. We back up our claim by comparing typical simulators and propose improvements to thermal simulators for future studies. Full article

Three-dimensional printing technology has emerged as a versatile and cost-effective alternative for the fabrication of electrochemical sensors. To enhance sensor sensitivity and biocompatibility, a diverse range of biocompatible and conductive materials can be employed in these devices. This allows these sensors to be modified to detect a wide range of analytes in various fields. 3D-printed electrochemical sensors have the potential to play a pivotal role in personalized medicine by enabling the real-time monitoring of metabolite and biomarker levels. These data can be used to personalize treatment strategies and optimize patient outcomes. The portability and low-cost nature of 3D-printed electrochemical sensors make them suitable for point-of-care (POC) diagnostics. These tests enable rapid and decentralized analyses, aiding in diagnosis and treatment decisions in resource-limited settings. Among the techniques widely reported in the literature for 3D printing, the fused deposition modeling (FDM) technique is the most commonly used for the development of electrochemical devices due to the easy accessibility of equipment and materials. Focusing on the FDM technique, this review explores the critical factors influencing the fabrication of electrochemical sensors and discusses potential applications in clinical analysis, while acknowledging the challenges that need to be overcome for its effective adoption. Full article

Background: Extracellular vesicles (EVs) derived from stem cells demonstrate significant potential in bone regeneration. Adipose tissue is regarded as a stem cell reservoir with abundant reserves and easy accessibility. Compared to adipose-derived stem cells (ASCs), dedifferentiated fat cells (DFATs) possess similar stem cell characteristics but exhibit greater proliferative capacity, higher homogeneity, and an enhanced osteogenic differentiation potential. This study is the first to examine the effect of DFATs-derived EVs on bone regeneration and elucidate their potential mechanisms of action. Methods: Primary DFATs were cultured using the “ceiling culture” method and EVs were isolated by ultracentrifugation and characterized. Experiments were performed to assess the impact of the EVs on the proliferation, migration, and osteogenesis of bone marrow mesenchymal stem cells (BMSCs). Subsequently, high-throughput miRNA sequencing was conducted on the EVs derived from DFATs that had undergone 0 days (0d-EVs) and 14 days (14d-EVs) of osteogenic differentiation. Results: The results indicated that the EVs derived from DFATs which experienced 14 days of osteogenic induction significantly promoted the proliferation, migration, and osteogenic differentiation of BMSCs. High-throughput sequencing results revealed that up-regulated miRNAs in the 14d-EVs were primarily involved in biological processes such as the Notch signaling pathway and the positive regulation of cell movement and migration. The target genes of these differently expressed miRNAs were enriched in osteogenesis-related signaling pathways. Conclusion: This study innovatively demonstrated that conditioned EVs (14d-EVs) derived from DFATs promoted the osteogenic differentiation of BMSCs via miRNAs, offering a promising cell-free therapeutic option for bone defect. Full article

The management of variety collections can be supported by integrating molecular data into Distinctness, Uniformity, and Stability (DUS) testing. DurdusTools is a genetic distance (GD) calculation tool that supports planning field trials in durum wheat. A commercially available single-nucleotide polymorphism (SNP) wheat microarray is used to profile varieties and candidate varieties. Their molecular profiles are stored in a database. SNP markers selected based on quality parameters are used to calculate the pairwise genetic distance (GD) between the varieties. Combining molecular and variety information creates a downloadable, user-friendly Excel-based output. The file shows the pairwise GD of the varieties most similar to the candidate variety of interest and selected variety information. After the first year of field trials, the DUS experts use the phenotypic assessment data together with the GD information to select genotypes to be grown in the field for side-by-side comparisons. The principles of DurdusTools allow for an easy integration of molecular data into DUS testing. Using the tool requires neither specific infrastructure nor molecular expert knowledge and was developed by its users for DUS testing purposes. This makes DurdusTools an easily accessible and user-friendly tool that supports variety selection for DUS field trials through an improved data basis. Full article

Background: Although computational models are advancing air quality prediction, achieving the desired performance or accuracy of prediction remains a gap, which impacts the implementation of machine learning (ML) air quality prediction models. Several models have been employed and some hybridized to enhance air quality and air quality index predictions. The objective of this paper is to systematically review machine and deep learning techniques for spatiotemporal air prediction challenges. Methods: In this review, a methodological framework based on PRISMA flow was utilized in which the initial search terms were defined to guide the literature search strategy in online data sources (Scopus and Google Scholar). The inclusion criteria are articles published in the English language, document type (articles and conference papers), and source type (journal and conference proceedings). The exclusion criteria are book series and books. The authors’ search strategy was complemented with ChatGPT-generated keywords to reduce the risk of bias. Report synthesis was achieved by keyword grouping using Microsoft Excel, leading to keyword sorting in ascending order for easy identification of similar and dissimilar keywords. Three independent researchers were used in this research to avoid bias in data collection and synthesis. Articles were retrieved on 27 July 2024. Results: Out of 374 articles, 80 were selected as they were in line with the scope of the study. The review identified the combination of a machine learning technique and deep learning techniques for data limitations and processing of the nonlinear characteristics of air pollutants. ML models, such as random forest, and decision tree classifier were among the commonly used models for air quality index and air quality predictions, with promising performance results. Deep learning models are promising due to the hyper-parameter components, which consist of activation functions suitable for nonlinear spatiotemporal data. The emergence of low-cost devices for data limitations is highlighted, in addition to the use of transfer learning and federated learning models. Again, it is highlighted that military activities and fires impact the O₃ concentration, and the best-performing models highlighted in this review could be helpful in developing predictive models for air quality prediction in areas with heavy military activities. Limitation: This review acknowledges methodological challenges in terms of data collection sources, as there are equally relevant materials on other online data sources. Again, the choice and use of keywords for the initial search and the creation of subsequent filter keywords limit the collection of other relevant research articles. Full article

The present work is devoted to the study of nonlinear vibrations of an electromagnetically actuated cantilever beam subject to harmonic external excitation. The soft actuator that controls the vibratory motion of such components of a robotic structure led to a strongly nonlinear governing differential equation, which was solved in this work by using a highly accurate technique, namely the Optimal Auxiliary Functions Method. Comparisons between the results obtained using our original approach with those of numerical integration show the efficiency and reliability of our procedure, which can be applied to give an explicit analytical approximate solution in two cases: the nonresonant case and the nearly primary resonance. Our technique is effective, simple, easy to use, and very accurate by means of only the first iteration. On the other hand, we present an analysis of the local stability of the model using Routh–Hurwitz criteria and the eigenvalues of the Jacobian matrix. Global stability is analyzed by means of Lyapunov’s direct method and LaSalle’s invariance principle. For the first time, the Lyapunov function depends on the approximate solution obtained using OAFM. Also, Pontryagin’s principle with respect to the control variable is applied in the construction of the Lyapunov function. Full article

Remote sensing change detection (RSCD) aims to utilize paired temporal remote sensing images to detect surface changes in the same area. Traditional CNN-based methods are limited by the size of the receptive field, making it difficult to capture the global features of remote sensing images. In contrast, Transformer-based methods address this issue with their powerful modeling capabilities. However, applying the Transformer architecture to image processing introduces a quadratic complexity problem, significantly increasing computational costs. Recently, the Mamba architecture based on state-space models has gained widespread application in the field of RSCD due to its excellent global feature extraction capabilities and linear complexity characteristics. Nevertheless, existing Mamba-based methods lack optimization for complex change areas, making it easy to lose shallow features or local features, which leads to poor performance on challenging detection cases and high-difficulty datasets. In this paper, we propose a Mamba-based RSCD network for difficult cases (DC-Mamba), which effectively improves the model’s detection capability in complex change areas. Specifically, we introduce the edge-feature enhancement (EFE) block and the dual-flow state-space (DFSS) block, which enhance the details of change edges and local features while maintaining the model’s global feature extraction capability. We propose a dynamic loss function to address the issue of sample imbalance, giving more attention to difficult samples during training. Extensive experiments on three change detection datasets demonstrate that our proposed DC-Mamba outperforms existing state-of-the-art methods overall and exhibits significant performance improvements in detecting difficult cases. Full article

Background/Objectives: In acute stroke, often-prolonged hospital transport times present an opportunity for early interventions to salvage brain tissue. Remote ischemic conditioning (RIC), where brief cycles of ischemia–reperfusion in a limb are induced to protect the brain, is a promising treatment for this setting. We assessed the usability of a novel RIC system in a simulated emergency response scenario. Methods: Paramedics were asked to use the RIC device in an emergency stroke care and ambulance transport simulation, overseen by a confederate. Feedback on device use was collected through questionnaires, including the System Usability Scale (SUS) and the NASA Task Load Index (NASA-TLX), and a semi-structured interview. Questionnaire responses were summarized using descriptive statistics; interview transcripts were analyzed thematically. Results: Nine paramedics (including the confederate) participated, with a mean of 10.0 ± 10.3 years of professional experience. Questionnaire responses indicated high device usability (mean SUS score: 85.3 ± 12.9 out of 100) and low task-related demands, effort, and frustration (mean NASA-TLX domain scores: ≤3.9 out of 20). Seven paramedics stated they would use the device in daily practice. They expressed concerns related to display screen clarity, interference with standard procedures, cable management, device fragility, and patient discomfort. Suggested improvements included adding indicators of device performance and refining the cuff design. Conclusions: While the device was considered easy to use, paramedics also identified important areas of improvement. With a small, localized study sample, our findings are primarily applicable to the refinement of the RICovery system for use in future clinical trials in the same healthcare setting. However, feedback on the importance of mitigating potential interference of newly introduced procedures with those already established, robustness of equipment, and effective paramedic–patient communication may also help inform the design of other pre-hospital interventions. Full article

The aim of this study was to evaluate the effects of mechanized final irrigation protocols (XPE, XP-Endo Finisher; XPC, XP-Clean; and ECL, Easy Clean) compared to PUI (passive ultrasonic irrigation) on the debris incidence and open dentinal tubules, and their effects on the adhesion interface after 48 h and 6 months. One hundred twenty maxillary central incisors were submitted to chemical–mechanical preparation using a rotary instrument and 2.5% sodium hypochlorite. Specimens were distributed in 4 groups (n = 30) in accordance with the mechanized final irrigation protocol: XPE, XPC, ECL, or PUI. Forty specimens (n = 10/group) were submitted to SEM analysis to evaluate the residue incidence and dentin open tubules. The other specimens were obturated using Bio-C Sealer and submitted to push-out bond strength and adhesive failure mode evaluations in the cervical, middle, and apical thirds after 48 h or 6 months (n = 10/group). Only in the apical third, ECL presented the highest residue incidence and fewer open dentinal tubules when compared to the XPE, XPC, and PUI groups (p < 0.05). In the cervical and middle root thirds, no significant differences were observed regardless of the group evaluated (p > 0.05). After 48 h, ECL resulted in the lowest bond strength only in the apical third (p < 0.05), while the XPE, XPC, and PUI groups remained similar in the cervical and middle thirds (p > 0.05). At 6 months, all groups showed lower bond strength values regardless of the root third evaluated, but ECL showed the lowest bond strength in the apical and middle root thirds when compared to the other groups (p < 0.05). The ECL protocol did not provide adequate residue removal on the apical radicular third and negatively affected the longevity of endodontic obturation using a calcium silicate-based sealer. Full article

This work describes the preparation of highly homogeneous thermoplastic starches (TPS’s) with the addition of 0, 5, or 10 wt.% of maltodextrin (MD) and 0 or 3 wt.% of TiO₂ nanoparticles. The TPS preparation was based on a two-step preparation protocol, which consisted in solution casting (SC) followed by melt mixing (MM). Rheology measurements at the typical starch processing temperature (120 °C) demonstrated that maltodextrin acted as a lubricating agent, which decreased the viscosity of the system. Consequently, the in situ measurement during the MM confirmed that the torque moments and real processing temperatures of all TPS/MD systems decreased in comparison with the pure TPS. The detailed characterization of morphology, thermomechanical properties, and local mechanical properties revealed that the viscosity decrease was accompanied by a slight decrease in the system homogeneity. The changes in the real processing temperatures might be quite moderate (ca 2–3 °C), but maltodextrin is a cheap and easy-to-add modifier, and the milder processing conditions are advantageous for both technical applications (energy savings) and biomedical applications (beneficial for temperature-sensitive additives, such as antibiotics). Full article

Due to the high cost of robots, the algorithm testing cost for physical robots is high, and the construction of motion control programs is complex, with low operation fault tolerance. To address this issue, this paper proposes a low-cost, cross-platform SCARA robot digital-twin simulation system based on the concept of digital twins. This method establishes a 5D architecture based on the characteristics of different platforms, classifies data and integrates functions, and designs a data-processing layer for motion trajectory calculation and data storage for a virtual-reality robot. To address the complexity of data interaction under different cross-platform communication forms, an editable, modular, cross-platform communication system is constructed, and various control commands are encapsulated into simple programming statements for easy invocation. Experimental results showed that, based on modular communication control, users can accurately control data communication and synchronous motion between virtual and physical models using simple command statements, reducing the development cost of control algorithms. Meanwhile, the virtual-robot simulation system, as a data mapping of the real experimental platform, accurately simulated the physical robot’s operating state and spatial environment. The robot algorithms tested using the virtual simulation system can be successfully applied to real robot platforms, accurately reproducing the operating results of the virtual system. Full article